Application of OSNA Nomogram in Patients With Macrometastatic Sentinel Lymph Node: A Retrospective Assessment of Accuracy.

Breast neoplasms axilla lymph node excision nomograms nucleic acid amplification techniques sentinel lymph node

Journal

Breast cancer : basic and clinical research
ISSN: 1178-2234
Titre abrégé: Breast Cancer (Auckl)
Pays: United States
ID NLM: 101474356

Informations de publication

Date de publication:
2021
Historique:
received: 28 08 2020
accepted: 14 04 2021
entrez: 17 5 2021
pubmed: 18 5 2021
medline: 18 5 2021
Statut: epublish

Résumé

Almost 50% to 70% of patients who undergo axillary lymph node dissection (ALND) because of a single metastatic sentinel lymph node (SLN) have no further metastatic nodes at the axillary histology. On these grounds, the one-step nucleic acid amplification (OSNA) nomogram was designed and validated. As a mathematical model, calculated through tumor size (expressed in millimeters) and CK19 mRNA copy number, it is thought to predict nonsentinel lymph node (NSLN) status. The aim of the study is to verify the diagnostic accuracy of the OSNA nomogram in a group of patients with macrometastatic SLN, with a retrospective analysis. The OSNA nomogram was retrospectively applied to a group of 66 patients with macrometastatic SLN who underwent ALND. The result of the final histology of the axillary cavity was compared to the nomogram prediction. We calculated the prevalence of NSLN metastasis in patients who underwent ALND, sensitivity and specificity, negative and positive predictive value of the nomogram. In patients with macrometastasis in SLN, the prevalence of patients with metastatic NSLN was 45%. The sensitivity of the nomogram was excellent (90%). The specificity was low (36%). Positive predictive value amounted to 54%, while negative predictive value was good (81%). These results suggest that the OSNA nomogram is a valid instrument that can help choose the best surgical strategy for the treatment of axillary cavity. The mathematical model is useful to avoid surgery in a selected group of patients because it accurately predicts NSLN status.

Identifiants

pubmed: 33994790
doi: 10.1177/11782234211014796
pii: 10.1177_11782234211014796
pmc: PMC8113365
doi:

Types de publication

Journal Article

Langues

eng

Pagination

11782234211014796

Informations de copyright

© The Author(s) 2021.

Déclaration de conflit d'intérêts

Declaration of conflicting interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Auteurs

Francesca Combi (F)

Clinical and Experimental Medicine, University of Modena and Reggio Emilia, Modena, Italy.

Alessia Andreotti (A)

Division of Breast Surgical Oncology, Department of Medical and Surgical Maternal-Infantile and Adult Sciences, University Hospital of Modena, Modena, Italy.

Anna Gambini (A)

Division of Breast Surgical Oncology, Department of Medical and Surgical Maternal-Infantile and Adult Sciences, University Hospital of Modena, Modena, Italy.

Enza Palma (E)

Division of Breast Surgical Oncology, Department of Medical and Surgical Maternal-Infantile and Adult Sciences, University Hospital of Modena, Modena, Italy.

Simona Papi (S)

Division of Breast Surgical Oncology, Department of Medical and Surgical Maternal-Infantile and Adult Sciences, University Hospital of Modena, Modena, Italy.

Alice Biroli (A)

Faculty of Medicine and Surgery, University of Modena and Reggio Emilia, Modena, Italy.

Stefania Zaccarelli (S)

Department of Pathology, University Hospital of Modena, Modena, Italy.

Guido Ficarra (G)

Department of Pathology, University Hospital of Modena, Modena, Italy.

Giovanni Tazzioli (G)

Division of Breast Surgical Oncology, Department of Medical and Surgical Maternal-Infantile and Adult Sciences, University Hospital of Modena, Modena, Italy.

Classifications MeSH